DBMS > AnzoGraph DB vs. Graph Engine vs. KeyDB vs. Snowflake

System Properties Comparison AnzoGraph DB vs. Graph Engine vs. KeyDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS
RDF store

Graph DBMS
Key-value store

Key-value store

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.graphengine.io

github.com/Snapchat/KeyDB
keydb.dev

www.snowflake.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

www.graphengine.io/docs/manual

docs.keydb.dev

docs.snowflake.net/manuals/index.html

Developer

Cambridge Semantics

Microsoft

EQ Alpha Technology Ltd.

Snowflake Computing Inc.

Initial release

2018

2010

2019

2014

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT License

Open Source

BSD-3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

C++

Server operating systems

Linux

.NET

Linux

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

by using the Redis Search module

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Python

C#
C++
F#
Visual Basic

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Lua

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

simple password-based access control and ACL

Users with fine-grained authorization concept, user roles and pluggable authentication

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